A comprehensive review of Value at Risk methodologies

P Abad, S Benito, C López - The Spanish Review of Financial Economics, 2014 - Elsevier
In this article we present a theoretical review of the existing literature on Value at Risk (VaR)
specifically focussing on the development of new approaches for its estimation. We effect a …

Frontiers in VaR forecasting and backtesting

MR Nieto, E Ruiz - International Journal of Forecasting, 2016 - Elsevier
The interest in forecasting the Value at Risk (VaR) has been growing over the last two
decades, due to the practical relevance of this risk measure for financial and insurance …

The realized volatility of commodity futures: Interconnectedness and determinants

E Bouri, B Lucey, T Saeed, XV Vo - International Review of Economics & …, 2021 - Elsevier
Using high frequency data and connectedness measures based on a time-varying
parameter vector autoregression (TVP-VAR) model, we study dynamic connectedness …

Systemic risk measurement: Multivariate GARCH estimation of CoVaR

G Girardi, AT Ergün - Journal of Banking & Finance, 2013 - Elsevier
We modify Adrian and Brunnermeier's (2011) CoVaR, the VaR of the financial system
conditional on an institution being in financial distress. We change the definition of financial …

Natural gas volatility prediction: Fresh evidence from extreme weather and extended GARCH-MIDAS-ES model

C Liang, Z **a, X Lai, L Wang - Energy Economics, 2022 - Elsevier
This study aims to analyzes the predictability of the natural gas volatility by considering
extreme weather information. Based on extended GARCH-MIDAS models, empirical results …

Value-at-risk prediction: A comparison of alternative strategies

K Kuester, S Mittnik, MS Paolella - Journal of Financial …, 2006 - academic.oup.com
Given the growing need for managing financial risk, risk prediction plays an increasing role
in banking and finance. In this study we compare the out-of-sample performance of existing …

Realising the future: forecasting with high‐frequency‐based volatility (HEAVY) models

N Shephard, K Sheppard - Journal of Applied Econometrics, 2010 - Wiley Online Library
This paper studies in some detail a class of high‐frequency‐based volatility (HEAVY)
models. These models are direct models of daily asset return volatility based on realised …

Forecasting daily variability of the S&P 100 stock index using historical, realised and implied volatility measurements

SJ Koopman, B Jungbacker, E Hol - Journal of Empirical Finance, 2005 - Elsevier
The increasing availability of financial market data at intraday frequencies has not only led to
the development of improved volatility measurements but has also inspired research into …

A power GARCH examination of the gold market

E Tully, BM Lucey - Research in International Business and Finance, 2007 - Elsevier
This paper investigates macroeconomic influences on gold using the asymmetric power
GARCH model (APGARCH) of [Ding, Z., Granger, CWJ, Engle, RF, 1993. Long memory …

Forecasting the volatility of crude oil futures using intraday data

B Sévi - European Journal of Operational Research, 2014 - Elsevier
We use the information in intraday data to forecast the volatility of crude oil at a horizon of 1–
66 days using a variety of models relying on the decomposition of realized variance in its …